Analytics Analyst

Surescripts

1d•$95,300 - $116,500•Hybrid

About The Position

The Analytics Analyst applies descriptive and prescriptive analytics to large-scale healthcare transaction data to generate actionable insights. As part of a cross-functional group, the Analyst works with analytics teammates, product, engineering, and commercial stakeholders. The role contributes to product discovery and delivers analyses, prototypes, dashboards, and narratives that inform product development and sales enablement. It calls for hands-on, careful, curious work that is reproducible and transparent. The Analyst executes analytics work under guidance, supports discovery and prototyping for products, helps develop recurring reporting and dashboards, and partners with engineering and product teams to understand and validate data. The position also involves documenting methods and assumptions, communicating findings to technical and non-technical audiences, and following privacy, governance, aggregation, and de-identification requirements. Surescripts uses a Flexible Hybrid Work model for most positions. Employees may work virtually and use offices as collaboration centers, with leadership alignment and agreement. Applicants must have unrestricted U.S. work authorization; the company does not provide work-visa sponsorship or support academic training or work-study programs requiring employer endorsement.

Requirements

Bachelor’s degree in data science, statistics, computer science, economics, public health, epidemiology, health economics, or a related field.
Working proficiency in SQL.
Working proficiency in Python or R for data cleaning, analysis, and automation; Python is preferred.
Hands-on experience regularly creating visualizations in at least one BI tool, such as Looker, Tableau, or Sigma, and applying descriptive analytics techniques such as summary statistics and basic trending.
Ability to manage data carefully, including joins, cohorting, profiling for completeness, missingness, and nulls, QA checks, spot-checks, versioning, and clear documentation.
Ability to explain results clearly, ask clarifying questions, and incorporate feedback.
Demonstrated ability to organize work, meet deadlines, and maintain quality in a dynamic environment.
Comfort using AI tools to support everyday analytics work.
Valid U.S. work authorization permitting work without restrictions; the company does not provide work-visa sponsorship.

Nice To Haves

At least 2 years of relevant analytics experience in healthcare, life sciences, payor/provider, PBM, or other data-rich environments; internship and co-op experience are welcomed.
Master’s degree.
Experience with healthcare data, ideally patient demographics, pharmacy fill data, pharmacy claims, medical claims, or prior authorization data.
Exposure to predictive analytics or modeling techniques.
Experience using AI tools in analytics, such as generative AI to build data-driven prototypes.
Experience with prototyping or whiteboarding tools such as Lucidchart, Miro, Figma, or Balsamiq.
Familiarity with ETL concepts and willingness to run and help modify existing processes.
Experience drafting slides or data reports for customer or stakeholder audiences and checking the accuracy of presented data.

Responsibilities

Execute analytics workstreams under guidance, including data extraction, cleaning, feature creation, exploratory analysis, and validation of results.
Build and maintain recurring reports and dashboards that communicate trends, performance signals, and product or customer insights.
Translate business questions into analytic tasks, including metric definitions, cohorts, time windows, and segmentation, with support from senior teammates.
Participate in product discovery for new products, supporting senior teammates and stakeholders as requirements take shape.
Explore and document available data sets, and build basic charts and prototypes to help stakeholders confirm needs before development.
Profile new data sources for completeness, missingness, and null values; perform basic quality checks and spot-check work.
Assist in building minimum viable products from agreed-upon prototypes.
Partner with data engineering and product and engineering teams to understand data structures, validate data quality, and align analytic outputs with product needs.
Understand existing ETL processes and help review or modify them to make source data analytics-ready.
Document assumptions, methodology, and code or queries to support reproducibility and auditability.
Contribute to internal and customer-facing presentations and data reports by producing clear visuals, concise narratives, and well-labeled outputs for technical and non-technical audiences, while ensuring presented data is accurate.
Follow rigorous data-handling standards for privacy, governance, aggregation, and de-identification, escalating questions when requirements are unclear.
Participate in team rituals such as intake, scoping, and reviews, and incorporate feedback to improve deliverable accuracy, clarity, and usability.